Automatic detection and reading of dangerous goods plates

In this paper, we present an efficient solution for automatic detection and reading of dangerous goods plates on trucks and trains. According to the ADR agreement dangerous goods transports are marked with an orange plate covering the hazard class and the identification number for the hazardous substances. Since under real-world conditions high resolution images (often at low quality) have to be processed an efficient and robust system is required. In particular, we propose a multi-stage system consisting of an acquisition step, a saliency region detector (to reduce the run-time), a plate detector, and a robust recognition step based on an Optical Character Recognition (OCR). To demonstrate the system, we show qualitative and quantitative localization/recognition results on two challenging data sets. In fact, building on proven robust and efficient methods, we show excellent detection and classification results under hard environmental conditions at low run-time.